Indirect estimation of the Convective Lognormal Transfer function model parameters for describing solute transport in unsaturated and undisturbed soil

2012 ◽  
Vol 132 ◽  
pp. 48-57 ◽  
Author(s):  
Mohammad Hossein Mohammadi ◽  
Marnik Vanclooster
Keyword(s):  
Transfer Function ◽  
Solute Transport ◽  
Model Parameters ◽  
Transfer Function Model ◽  
Function Model ◽  
Undisturbed Soil ◽  
Indirect Estimation

A Transfer Function Model of Solute Transport Through Soil: 2. Illustrative Applications

1986 ◽  
Vol 22 (2) ◽  
pp. 248-254 ◽  
Author(s):  
Robert E. White ◽  
Jeremy S. Dyson ◽  
Rosalyn A. Haigh ◽  
William A. Jury ◽  
Garrison Sposito
Keyword(s):  
Transfer Function ◽  
Solute Transport ◽  
Transfer Function Model ◽  
Function Model

A Transfer Function Model of Solute Transport Through Soil: 1. Fundamental Concepts

1986 ◽  
Vol 22 (2) ◽  
pp. 243-247 ◽  
Author(s):  
William A. Jury ◽  
Garrison Sposito ◽  
Robert E. White
Keyword(s):  
Transfer Function ◽  
Solute Transport ◽  
Transfer Function Model ◽  
Function Model

A Transfer Function Model of Solute Transport Through Soil: 3. The Convection-Dispersion Equation

1986 ◽  
Vol 22 (2) ◽  
pp. 255-262 ◽  
Author(s):  
Garrison Sposito ◽  
Robert E. White ◽  
Peter R. Darrah ◽  
William A. Jury
Keyword(s):  
Transfer Function ◽  
Solute Transport ◽  
Dispersion Equation ◽  
Transfer Function Model ◽  
Function Model

The Parameters Identification of Airplane Flutter Model Based Global Nonlinear Separable Least Square Method

2012 ◽  
Vol 490-495 ◽  
pp. 2774-2779
Author(s):  
Jie Yao ◽  
Jian Hong Wang
Keyword(s):  
Transfer Function ◽  
Least Square Method ◽  
Least Square ◽  
Model Parameters ◽  
Transfer Function Model ◽  
Input Output ◽  
Function Model ◽  
Output Data ◽  
Noisy Input ◽  
Least Square Problem

considering the noisy input-output data, this paper come up with an idea extending the deviation compensation least square (CLS)to the nonlinear separable least square (NSLS).The least square method employed nonlinear separable least square adaptive to the noisy situation is able to identify accurately the airplane flutter model parameters. Combining the transfer function model, this algorithm successfully converts the identification of noisy system into nonlinear separable least square problem. The square deviation of two noises and the model parameter of the transfer function can be estimated separately by using of above algorithm.

Statistical Determination of Bit-Rock Interaction and Drill String Mechanics for Automatic Drilling Optimization

2020 ◽  
Author(s):  
Adrian Ambrus ◽  
Benoît Daireaux ◽  
Liv A. Carlsen ◽  
Rodica G. Mihai ◽  
Mohsen Karimi Balov ◽  
...  
Keyword(s):  
Transfer Function ◽  
Dynamic Models ◽  
Drill String ◽  
Model Parameters ◽  
Drilling Process ◽  
Transfer Function Model ◽  
Transient Effects ◽  
Model Approximation ◽  
Function Model ◽  
Rock Interaction

Abstract The ability to predict the response of a drill bit to the topside axial and rotational velocities of the drill-string is a prerequisite for any system aimed at automatically controlling the drilling parameters to optimize the rate of penetration and the overall quality of the well construction process. When drilling with a Polycrystalline Diamond Compact (PDC) bit, even the steady-state response can exhibit complex behavior, characterized by the presence of (at least) three different regimes whose range and parameters depend upon the bit characteristics and the mechanical properties of the formations being drilled. Transient effects significantly complicate the situation, especially when vibrations (axial, rotational or lateral) disturb the drilling process. Often, the root cause of these vibrations lies in the bit-rock interaction itself, while the drill string, through its elasticity and interaction with the borehole wall, may amplify or attenuate these vibrations. Therefore, continuous calibration of the drill string and bit-rock parameters from available surface and downhole measurements is critical for any automated control system relying on dynamic models of the drilling process. We present a calibration procedure whose goal is two-fold: first, to identify the time-varying parameters involved in the bit-rock interaction, and second, to provide a low-order, transfer function model approximation of the drill string axial and rotational dynamics. Our approach is based on particle filter techniques and a refined instrumental variable method for transfer function model estimation, and allows for real-time estimation of the various model parameters. We illustrate its behavior against recorded drilling data, where the proposed methods are shown to capture the different dynamics in place. We explain, in addition, how the calibrated drill string and bit-rock interaction models can be integrated in a framework to identify drilling parameter regions prone to axial or rotational vibrations.

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